S1-Omni: A Unified Multimodal Reasoning Model for Scientific Understanding, Prediction, and Generation
We present S1-Omni, a unified multimodal reasoning model for scientific understanding, prediction, and generation. AI for Science (AI4S) has advanced significantly through domain-specific models, tool-augmented LLMs, and scientific language models. However, model capabilities remain highly fragmented, limiting the joint modeling of heterogeneous data, scientific laws, and expert knowledge. S1-Omni addresses this gap by consolidating these capabilities into a single, coherent scientific reasoning model. The architecture of S1-Omni is built upon three core components: unified representation of scientific data, natural-world knowledge alignment, and decoding for domain-specific tasks. First,...
| Authors | Jiahao Zhao, Junyi Liu, Lifeng Xu et al. |
|---|---|
| Primary category | cs.AI |
| Published | 17 July 2026 |
| Last updated at source | 17 July 2026 |
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